Senior Data Scientist

Posted 15 Days Ago
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Hyderabad, Telangana, IND
In-Office
Senior level
HR Tech
The Role
Leads the design, development, testing, and production delivery of AI agents and agentic workflows. Applies data science, machine learning, statistical modeling, Python, and SQL to solve business problems. Integrates AI solutions with enterprise platforms, APIs, databases, cloud services, and governed data. Establishes evaluation, observability, security, responsible AI, CI/CD, monitoring, and optimization practices while collaborating with technical, business, legal, security, and compliance teams.
Summary Generated by Built In

TriNet is a leading provider of comprehensive human resources solutions for small to midsize businesses (SMBs). We enhance business productivity by enabling our clients to outsource their HR function to one strategic partner and focus on operating and growing their core businesses. Our full-service HR solutions include payroll processing, human capital consulting, employment law compliance and employee benefits, including health insurance, retirement plans and workers’ compensation insurance.

TriNet has a nationwide presence and an experienced executive team. Our stock is publicly traded on the NYSE under the ticker symbol TNET. If you are passionate about innovation and making an impact on the large SMB market, join us as we power our clients’ business success with extraordinary HR.

Do not meet every single requirement? Studies have shown that many potential applicants discourage themselves from applying to jobs unless they meet every single requirement. TriNet always strives to hire the most qualified candidate for a particular role, ensuring we deliver outstanding results for our small and medium-size customers. So if you're excited about this role but your past experience doesn't align perfectly with every single qualification in the job description, nobody’s perfect – and we encourage you to apply. You may just be the right candidate for this or other roles.

A Brief Overview:

This is a high-impact, execution-focused role responsible for building and delivering AI-powered agents and agentic workflows that address critical business challenges. The role combines strong applied data science foundations with hands-on delivery using commonly used technology ecosystems, including Anthropic Claude on AWS Bedrock, Claude Code, Microsoft Copilot, GitHub Copilot and related frameworks and observability tools.

You will partner with Data & Analytics leaders and cross-functional teams to design and deliver scalable, secure, and compliant AI solutions in enterprise environments. This role is ideal for someone who excels at translating business needs into clear requirements and delivering high-quality AI agents that operate reliably within real-world workflows.

Key Responsibilities:

Agentic AI Solution Design and Delivery

  • Lead the design, development and testing of single-agent and multi-agent solutions using LLMs, prompt and context engineering, retrieval-augmented generation (RAG), tool use and structured outputs.
  • Translate business problems into agent goals, workflow logic, system interactions, acceptance criteria, exception handling and human-in-the-loop controls.
  • Integrate agents with enterprise platforms, APIs, MCP servers, databases, SaaS applications and governed data sources to enable secure end-to-end workflow execution.
  • Build and optimise retrieval, grounding, memory and orchestration patterns that improve accuracy, traceability and task completion.
  • Establish evaluation and observability practices covering quality, groundedness, safety, latency, cost, failure modes and regression testing.
  • Productionise solutions through source control, automated testing, deployment, release validation, monitoring, issue triage and continuous optimisation.
     

Applied Data Science and Machine Learning

  • Frame business problems as analytical, statistical, machine learning or agentic AI use cases, selecting the simplest effective approach.
  • Prepare structured and unstructured data and perform feature engineering, model development, validation and error analysis using reproducible Python and SQL workflows.
  • Design experiments and measurement approaches to demonstrate model performance, incremental value and business impact.

Collaboration, Governance and Leadership:

  • Partner with Product, Engineering, Security, Legal, Compliance and business teams to define priorities, dependencies, controls and acceptance criteria.
  • Embed responsible AI practices, including access controls, privacy protections, guardrails, human oversight, fallback mechanisms and audit-ready logging.
  • Drive strong engineering and analytical standards through modular design, code quality, peer review, testing discipline and clear documentation.
  • Communicate implementation choices, analytical findings, limitations, delivery risks and production readiness to technical and non-technical stakeholders.
  • Provide technical guidance and contribute reusable patterns, evaluation assets and delivery standards across Data & Analytics.
     

Required Qualifications Education:

  • Bachelor’s degree in Computer Science, Data Science, Statistics, Mathematics, Engineering or a related quantitative field. A master’s degree is preferred.
     

Must-Have Experience:

  • 6+ years of experience in data science, machine learning, applied AI or software engineering, including delivery of production solutions.
  • Hands-on experience building LLM-powered applications or agents using prompt and context engineering, RAG, tool or function calling, orchestration and structured evaluation.
  • Experience implementing multi-step workflows with enterprise integrations, exception handling, state management and human-in-the-loop activities.
  • Strong Python and SQL skills, with experience writing maintainable, testable and reusable code.
  • Experience integrating applications with APIs, databases, vector stores, cloud services and enterprise data sources.
  • Experience operationalising AI or machine learning solutions through Git-based source control, CI/CD, testing, deployment, monitoring and ongoing optimisation.
  • Working knowledge of statistical modelling, machine learning, experimental design and model validation.
  • Ability to deliver complex solutions with limited oversight and collaborate effectively across technical and business teams.

Preferred Experience:

  • Experience with Anthropic Claude and AWS Bedrock, including model access, knowledge bases, agents, guardrails and enterprise integrations.
  • Experience building enterprise agents with Microsoft Copilot or Copilot Studio and connecting them to Microsoft 365, Power Platform or business applications.
  • Experience using Claude Code and GitHub Copilot to accelerate software development while maintaining code quality and engineering controls.
  • Experience with LangChain, LangGraph or similar orchestration frameworks, and Langfuse or comparable evaluation and observability tooling.
  • Experience with vector databases, semantic search, document processing, multi-agent patterns and adversarial or red-team testing.
  • Experience applying predictive modelling, natural language processing, optimisation, time-series forecasting or recommendation methods.
     

Skills and Abilities:

  • Agentic AI and LLM Engineering: Strong understanding of RAG, tool use, orchestration, memory, structured outputs, context engineering and agent evaluation.
  • Data Science and Statistics: Strong grounding in data exploration, feature engineering, statistical reasoning, machine learning, experimentation and validation.
  • Software and Data Engineering: Ability to build production-quality Python and SQL solutions and integrate them with governed enterprise systems.
  • LLMOps, MLOps and DevOps: Familiarity with version control, testing, deployment pipelines, observability, monitoring and release management.
  • Responsible AI and Security: Ability to design controls for privacy, safety, transparency, data protection, auditability and human oversight.
  • Problem Solving, Communication and Ownership: Ability to structure ambiguous problems, make evidence-based trade-offs and lead delivery across functions.
     

Certifications:

  • Relevant agentic AI, generative AI, AWS, data science, machine learning, MLOps or responsible AI certifications are advantageous but not required.
     

TravelRequirements:

  • Minimal travel required.
     

Work Environment

  • Work in a clean, pleasant, and comfortable office work setting. The work environment characteristics described here are representative of those an employee encounters while performing the essential functions of this job. Reasonable accommodations may be made to enable persons with disabilities to perform the essential functions.
  • This position is 100% in office.
     

Please Note: TriNet reserves the right to change or modify job duties and assignments at any time. The above job description is not all encompassing. Position functions and qualifications may vary depending on business necessity.

TriNet is an Equal Opportunity Employer and does not discriminate against applicants based on race, religion, color, disability, medical condition, legally protected genetic information, national origin, gender, sexual orientation, marital status, gender identity or expression, sex (including pregnancy, childbirth or related medical conditions), age, veteran status or other legally protected characteristics. Any applicant with a mental or physical disability who requires an accommodation during the application process should contact [email protected] to request such an accommodation. 

Skills Required

  • Bachelor's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related quantitative field
  • 6+ years of experience in data science, machine learning, applied AI, or software engineering, including production solution delivery
  • Hands-on experience building LLM-powered applications or agents using prompt and context engineering, RAG, tool or function calling, orchestration, and structured evaluation
  • Experience implementing multi-step workflows with enterprise integrations, exception handling, state management, and human-in-the-loop activities
  • Strong Python and SQL skills with experience writing maintainable, testable, and reusable code
  • Experience integrating applications with APIs, databases, vector stores, cloud services, and enterprise data sources
  • Experience operationalizing AI or machine learning solutions through Git-based source control, CI/CD, testing, deployment, monitoring, and ongoing optimization
  • Working knowledge of statistical modeling, machine learning, experimental design, and model validation
  • Ability to deliver complex solutions with limited oversight and collaborate across technical and business teams
  • Master's degree in a quantitative field
  • Experience with Anthropic Claude and AWS Bedrock, including model access, knowledge bases, agents, guardrails, and enterprise integrations
  • Experience building enterprise agents with Microsoft Copilot or Copilot Studio and connecting them to Microsoft 365, Power Platform, or business applications
  • Experience using Claude Code and GitHub Copilot while maintaining code quality and engineering controls
  • Experience with LangChain, LangGraph, Langfuse, or comparable orchestration, evaluation, and observability tools
  • Experience with vector databases, semantic search, document processing, multi-agent patterns, and adversarial or red-team testing
  • Experience applying predictive modeling, natural language processing, optimization, time-series forecasting, or recommendation methods
  • Relevant agentic AI, generative AI, AWS, data science, machine learning, MLOps, or responsible AI certifications

TriNet Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about TriNet and has not been reviewed or approved by TriNet.

  • Healthcare Strength — Access to major national and regional carriers (e.g., Aetna, Kaiser, select Blue plans, and UnitedHealthcare in many states) and multiple plan designs underpin strong health coverage. Consolidated enrollment tools and recognizable networks help many teams view total rewards favorably.
  • Retirement Support — A TriNet-sponsored multiple-employer 401(k) administered with Empower simplifies setup and payroll integration. Fiduciary and administrative responsibilities handled by the provider add tangible value to retirement offerings.
  • Flexible Benefits — A broad menu spans medical, dental, vision, life/disability, FSA/HSA, EAP, commuter, and other voluntary options with side-by-side plan comparisons and open-enrollment support. Access to add-ons like telemedicine and wellness perks in one platform expands choice for varied workforce needs.

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The Company
HQ: Dublin, California
4,405 Employees

What We Do

TriNet (NYSE: TNET) provides small and medium-size businesses (SMBs) with full-service HR solutions tailored by industry. To free SMBs from HR complexities, TriNet offers access to human capital expertise, benefits, risk mitigation and compliance, payroll and real-time technology. From Main Street to Wall Street, TriNet empowers SMBs to focus on what matters most—growing their business.

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